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AMC
2006

Parallel preconditioned conjugate gradient optimization of the Rayleigh quotient for the solution of sparse eigenproblems

13 years 11 months ago
Parallel preconditioned conjugate gradient optimization of the Rayleigh quotient for the solution of sparse eigenproblems
A parallel algorithm based on the multidimensional minimization of the Rayleigh quotient is proposed to evaluate the leftmost eigenpairs of the generalized symmetric positive definite eigenproblem. The minimization is performed via a conjugate gradient-like procedure accelerated by a factorized approximate inverse preconditioner (FSAI) and by a number of block preconditioners. The resulting code obtains a high level of parallel efficiency and proves to be comparable with the PARPACK package on a set of large matrices arising from various discretizations of PDEs of elliptic/parabolic type.
Luca Bergamaschi, Angeles Martinez, Giorgio Pini
Added 10 Dec 2010
Updated 10 Dec 2010
Type Journal
Year 2006
Where AMC
Authors Luca Bergamaschi, Angeles Martinez, Giorgio Pini
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